Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "77" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 31 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 31 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2460014 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 61.330561 | 9.642761 | 0.388618 | -0.442270 | 5.060467 | 5.440378 | 15.441628 | 45.068155 | 0.2609 | 0.4998 | 0.3515 | nan | nan |
| 2460013 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 59.347563 | 21.582609 | 0.705256 | -0.421261 | 3.273586 | 1.015151 | 8.278825 | -0.834775 | 0.2991 | 0.4766 | 0.2893 | nan | nan |
| 2460012 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 56.879629 | 20.800596 | 0.587387 | -0.559432 | 3.595604 | 1.514530 | 7.801606 | 0.469781 | 0.2999 | 0.4779 | 0.2853 | nan | nan |
| 2460011 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 57.584179 | 20.464664 | 0.706280 | -0.634297 | 8.032099 | 2.831852 | 3.844834 | 0.104127 | 0.3167 | 0.4896 | 0.2887 | nan | nan |
| 2460010 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 66.469759 | 28.203584 | 0.882812 | -0.403991 | 5.708339 | 3.190450 | 5.539575 | -0.204894 | 0.3008 | 0.4699 | 0.2644 | nan | nan |
| 2460009 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 58.907355 | 25.807828 | 0.763320 | -0.553379 | 5.271019 | 2.634376 | -0.043162 | -0.033223 | 0.3259 | 0.4674 | 0.2454 | nan | nan |
| 2460008 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 68.989114 | 31.374389 | 0.803177 | -0.631616 | 3.978584 | 2.761654 | 1.686106 | 0.316197 | 0.3858 | 0.5274 | 0.2250 | nan | nan |
| 2460007 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 55.692079 | 23.022030 | 0.729340 | -0.604763 | 3.989576 | 1.690233 | 0.641210 | -0.871874 | 0.3222 | 0.4869 | 0.2638 | nan | nan |
| 2459999 | not_connected | 0.00% | 94.82% | 86.30% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.1056 | 0.1672 | 0.1006 | nan | nan |
| 2459998 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 50.901353 | 21.864061 | 0.623155 | -0.414150 | 6.408294 | 3.500235 | 5.324037 | 1.423131 | 0.2974 | 0.4672 | 0.2762 | nan | nan |
| 2459997 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 56.123016 | 24.392577 | 0.787791 | -0.332267 | 4.943794 | 3.044862 | 20.864866 | -0.802532 | 0.3175 | 0.4884 | 0.2787 | nan | nan |
| 2459996 | not_connected | 100.00% | 99.57% | 99.62% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | 0.3717 | 0.3259 | 0.3251 | nan | nan |
| 2459995 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 58.692481 | 25.166878 | 0.624796 | -0.561563 | 4.013156 | 2.245171 | 4.325918 | 0.463186 | 0.3226 | 0.4971 | 0.2838 | nan | nan |
| 2459994 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 56.667369 | 22.305237 | 0.557749 | -0.511996 | 4.080003 | 2.372629 | 1.906752 | -0.067582 | 0.3221 | 0.5088 | 0.3054 | nan | nan |
| 2459993 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 58.984192 | 21.209635 | 0.513769 | -0.239435 | 5.388824 | 4.871704 | 3.872342 | 20.769191 | 0.3144 | 0.5219 | 0.3279 | nan | nan |
| 2459991 | not_connected | 100.00% | 99.89% | 99.95% | 0.00% | - | - | 264.385859 | 264.810852 | inf | inf | 3074.885065 | 3091.427598 | 6322.626448 | 6175.430651 | 0.3170 | 0.2781 | 0.3339 | nan | nan |
| 2459990 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 47.388440 | 17.642746 | 0.316416 | -0.346452 | 3.719627 | 5.502731 | 6.726533 | 10.952941 | 0.3585 | 0.5191 | 0.3070 | nan | nan |
| 2459989 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 42.659091 | 6.523829 | 0.271497 | -0.087287 | 3.399761 | 1.697578 | 8.245590 | 19.086727 | 0.3971 | 0.5706 | 0.3557 | nan | nan |
| 2459988 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 57.802326 | 19.865860 | 0.296541 | -0.223733 | 7.525587 | 6.078660 | 11.328214 | 11.695647 | 0.3572 | 0.5182 | 0.3077 | nan | nan |
| 2459987 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 51.962875 | 12.723302 | 0.444674 | -0.276593 | 5.097496 | 1.879296 | 1.734070 | 2.904085 | 0.3605 | 0.5543 | 0.3466 | nan | nan |
| 2459986 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 60.693499 | 6.907526 | 0.554146 | -0.091045 | 3.952388 | 2.316870 | 3.771266 | 4.783647 | 0.3826 | 0.6063 | 0.3564 | nan | nan |
| 2459985 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 61.912742 | 22.326964 | 0.502595 | -0.484615 | 4.427797 | 3.436644 | -0.216355 | 14.873141 | 0.3203 | 0.5116 | 0.3228 | nan | nan |
| 2459984 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 58.945225 | 26.679514 | 0.574541 | -0.570484 | 6.002112 | 5.367520 | 3.379624 | 2.665035 | 0.3328 | 0.4962 | 0.2689 | nan | nan |
| 2459983 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 63.219148 | 9.431093 | 0.752740 | -0.219672 | 5.447846 | 5.765141 | 5.116805 | 19.486808 | 0.3337 | 0.6028 | 0.3551 | nan | nan |
| 2459982 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 51.690036 | 9.262623 | 0.296274 | -1.002069 | 2.573616 | 3.350638 | 0.308495 | -0.420796 | 0.4628 | 0.6146 | 0.2645 | nan | nan |
| 2459981 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 49.559531 | 13.139176 | 0.620559 | -0.468244 | 4.924972 | 6.993290 | 7.544838 | 24.596214 | 0.3258 | 0.5383 | 0.3425 | nan | nan |
| 2459980 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 48.202099 | 17.801727 | 0.338622 | -0.864666 | 4.485468 | 6.692344 | 3.158193 | 1.197523 | 0.4135 | 0.5637 | 0.2578 | nan | nan |
| 2459979 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 59.679678 | 0.695916 | 0.493422 | -0.609698 | 6.015690 | -0.958360 | 17.305420 | 0.199391 | 0.2792 | 0.6016 | 0.4454 | nan | nan |
| 2459978 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 58.734571 | 0.736918 | 0.552355 | -0.437296 | 8.125045 | -0.638337 | 17.634925 | 0.183354 | 0.2864 | 0.5941 | 0.4364 | nan | nan |
| 2459977 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 48.619540 | 0.883187 | 0.374890 | -0.580480 | 5.897669 | -0.898986 | 11.326788 | -0.277272 | 0.3279 | 0.5665 | 0.3696 | nan | nan |
| 2459976 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 59.724987 | 0.823858 | 0.573878 | -0.507664 | 4.962520 | -1.066140 | 12.025267 | -0.693653 | 0.2882 | 0.6098 | 0.4464 | nan | nan |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 61.330561 | 61.330561 | 9.642761 | 0.388618 | -0.442270 | 5.060467 | 5.440378 | 15.441628 | 45.068155 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 59.347563 | 59.347563 | 21.582609 | 0.705256 | -0.421261 | 3.273586 | 1.015151 | 8.278825 | -0.834775 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 56.879629 | 56.879629 | 20.800596 | 0.587387 | -0.559432 | 3.595604 | 1.514530 | 7.801606 | 0.469781 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 57.584179 | 57.584179 | 20.464664 | 0.706280 | -0.634297 | 8.032099 | 2.831852 | 3.844834 | 0.104127 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 66.469759 | 66.469759 | 28.203584 | 0.882812 | -0.403991 | 5.708339 | 3.190450 | 5.539575 | -0.204894 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 58.907355 | 58.907355 | 25.807828 | 0.763320 | -0.553379 | 5.271019 | 2.634376 | -0.043162 | -0.033223 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 68.989114 | 31.374389 | 68.989114 | -0.631616 | 0.803177 | 2.761654 | 3.978584 | 0.316197 | 1.686106 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 55.692079 | 55.692079 | 23.022030 | 0.729340 | -0.604763 | 3.989576 | 1.690233 | 0.641210 | -0.871874 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 50.901353 | 50.901353 | 21.864061 | 0.623155 | -0.414150 | 6.408294 | 3.500235 | 5.324037 | 1.423131 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 56.123016 | 56.123016 | 24.392577 | 0.787791 | -0.332267 | 4.943794 | 3.044862 | 20.864866 | -0.802532 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 58.692481 | 58.692481 | 25.166878 | 0.624796 | -0.561563 | 4.013156 | 2.245171 | 4.325918 | 0.463186 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 56.667369 | 56.667369 | 22.305237 | 0.557749 | -0.511996 | 4.080003 | 2.372629 | 1.906752 | -0.067582 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 58.984192 | 58.984192 | 21.209635 | 0.513769 | -0.239435 | 5.388824 | 4.871704 | 3.872342 | 20.769191 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Power | inf | 264.385859 | 264.810852 | inf | inf | 3074.885065 | 3091.427598 | 6322.626448 | 6175.430651 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 47.388440 | 17.642746 | 47.388440 | -0.346452 | 0.316416 | 5.502731 | 3.719627 | 10.952941 | 6.726533 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 42.659091 | 6.523829 | 42.659091 | -0.087287 | 0.271497 | 1.697578 | 3.399761 | 19.086727 | 8.245590 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 57.802326 | 19.865860 | 57.802326 | -0.223733 | 0.296541 | 6.078660 | 7.525587 | 11.695647 | 11.328214 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 51.962875 | 51.962875 | 12.723302 | 0.444674 | -0.276593 | 5.097496 | 1.879296 | 1.734070 | 2.904085 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 60.693499 | 6.907526 | 60.693499 | -0.091045 | 0.554146 | 2.316870 | 3.952388 | 4.783647 | 3.771266 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 61.912742 | 22.326964 | 61.912742 | -0.484615 | 0.502595 | 3.436644 | 4.427797 | 14.873141 | -0.216355 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 58.945225 | 58.945225 | 26.679514 | 0.574541 | -0.570484 | 6.002112 | 5.367520 | 3.379624 | 2.665035 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 63.219148 | 63.219148 | 9.431093 | 0.752740 | -0.219672 | 5.447846 | 5.765141 | 5.116805 | 19.486808 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 51.690036 | 51.690036 | 9.262623 | 0.296274 | -1.002069 | 2.573616 | 3.350638 | 0.308495 | -0.420796 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 49.559531 | 13.139176 | 49.559531 | -0.468244 | 0.620559 | 6.993290 | 4.924972 | 24.596214 | 7.544838 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 48.202099 | 17.801727 | 48.202099 | -0.864666 | 0.338622 | 6.692344 | 4.485468 | 1.197523 | 3.158193 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 59.679678 | 59.679678 | 0.695916 | 0.493422 | -0.609698 | 6.015690 | -0.958360 | 17.305420 | 0.199391 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 58.734571 | 0.736918 | 58.734571 | -0.437296 | 0.552355 | -0.638337 | 8.125045 | 0.183354 | 17.634925 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 48.619540 | 48.619540 | 0.883187 | 0.374890 | -0.580480 | 5.897669 | -0.898986 | 11.326788 | -0.277272 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 77 | N06 | not_connected | ee Shape | 59.724987 | 0.823858 | 59.724987 | -0.507664 | 0.573878 | -1.066140 | 4.962520 | -0.693653 | 12.025267 |